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Wednesday, December 11, 2019

DOC: 'Cartography for Digital Technology Investment, Part 1

By Mark P. Dangelo
September 23, 2019

Topics:
Mark Dangelo
Technology
Innovation


MarkDangelo(Mark P. Dangelo is president of MPD Organizations LLC, featuring books, industry reports and articles. He is a strategic management consultant, outsourcing advisor and analytics specialist with extensive process, technology and financial results and is a frequent contributor to MBA Insights. He can be reached at mark@mpdangelo.com or at 440/725-9402.)

It is too easy to believe in innovation (e.g., e-solution sets, AI LOSs, the 5-Vs of data) as the cure-all--unless we understand the interactions between our technological prescriptions. Our love affair with "everything new" can lead to financial disaster and missed opportunities. In a financial services and banking organization era defined by digitization and automation, have you ever wondered beyond costs, why the urgent imperative of efficiencies and big data dominates our budgets and executive discussions? When we examine the returns on our investments (e.g., NPV, ROI, ROE, CR, margins), are the solutions (e.g., AI, machine learning, RPA/process automation) more important than iterative business drivers?

Questions are NOT Passive-Aggressiveness in Disguise
As I pore over hourly headlines, news feeds and industry reports, the communications convey "axioms" that the solutions, as a means of market differentiation, were the catalysts for enterprise success or in some cases, THE victory. Prior to the start of the 4th Industrial Revolution, we would label that technology for the sake of technology. Yet, even today, the accomplishment is only distinctive until a competitor copied or exceed the prized solution using one of their own, often with different partners and delivering solutions in shorter timeframes. It resembles a childhood game of leapfrog as competitor's springboard "off the back" of your results to arrive in front of you--quite frustrating and very expensive--and the cycle begins anew across a landscape veiled in fog.

Yet, have we ever asked why? Is it because technology and automation drive profits so our institutions must be leaders? Well, yes. It is because consumers demand shorter timeframes and improved quality of service all the while adjusting their behaviors and wants? Yes, that is also true. Is it because competitive intelligence and market distinction demands advancement in the product and service offerings lest your enterprise be labeled a "dementasaurus" (a demented, old dinosaur) and not a "shalofolofolus" (the coolest dinosaur)? That is a big, "of course."

Nonetheless, these still do not provide the critical driver that should be part of every financial institution's corporate mission statement and objectives--cross-linked channels, often strategically labeled during banking transformations as digital omnichannels. So, in this era of growing synthetic intelligences, the misuse of terms such as AI, RPA, MI and DL, there is a demand to ground these "solutions" as a matrixed part of customer contact, back-office processing, use-cases and technological sophistication (including cybersecurity and e-currencies). A rationale for misuse increasingly resides in not comprehending the DOC.

As traditional and non-traditional financial institutions prepare their 2020 budgets, the approval of initiatives might be better served when mapped (for lack of a better word) across these DOCs to reduce overlap, rationalize applications, streamline vendors, deliver training and educations and most importantly, how each component, each solution building block, contributes to profits, margins and distinction. We love our innovations, but creation of digital omnichannel (#DOC) delivery layers (tied to how, when and where used) ensures that the chasing of customers and competitors aligns with organizational needs and goals. A very simplistic analogy is to think of this concept as creation of digital Lego building blocks each having a purpose in the delivery of a solution.

Digital Omnichannel Starting Points, Industry Perceptions and Assumptions
Let's step back for a minute as we prepare our DOC maps. The mortgage environment often appears to be a self-contained industry, spread across a select group of individuals and firms aiding with financing and terms that not only benefit the homeowner, but also those capital and technology investors seeking to streamline processes, lower costs and improve shrinking margins.

More importantly, rapid advances in data and risk attribution have reinstated faith in lending institutions and their role in serving the consumer. Many within the industry, and across those analysts who study industry health, attest that the mortgage industry measured against accepted benchmarks seems to be in good shape. Examples of technological progress include LOSs that are being integrated with multiple layers of machine intelligence solutions with the results being outstanding accuracy, reduced timings, improved data exchanges, supply-chain integrations, predictable profits and loyal homeowners.

The outstanding balances of all domestic residential mortgages now exceeds $9.5 trillion--a high water mark not seen since the meltdown of 2008. Indeed, the outstanding amount is spread out over fewer whole loans, "qualified" buyers, and underpinned by data analytics (along with vast amounts of source data) that would have been a "dream" during the last industry correction and subsequent litigations.

Lately, there are bond and equity market "health" indicators that are precipitating concerns among financial managers and investment specialists. From obscure yield curve inversions, to quality of consumer debt, to domestic and international growth, to national debt versus GDP, cautionary limits are being breached in the face of caustic political dialogues. As these aberrations surface, strength in lending is only tempered by the decade old disposition quandary of what to do with GSE conservatorship, the lack of private securitizations and asset instruments and a stalling or removal of consumer protections (e.g., Dodd-Frank, CPFB).

Yet, homeownership delinquency rates remain steady and low. While nagged by a lack of "starter homes" for first-time home borrowers, refinancing has risen sharply as rates have declined and expectations of future equity increases are buoyed by rising home prices. However, a trend that many disagree on its significance are the increases in new apartment (multifamily) construction and its impacts on future homeownership.

As markets and economies struggle, will this be a case where the mortgage industry and its channels of outreach are isolated from macro industry forces, or is contagion on the horizon as 2020 dawns? Will political parties recognize that their words are translating into market and economic consequences, or will industries, worrying about the optics, suffer at the hands of a few? Will our emerging use of advanced analytics, snowflake data (i.e., non-pejorative attribution), machine learning, usher in a new age of stability and risk-attributed consumers or will it be a false-positive that causes a retrenchment?

However, what the potential solution determination requires, before we prescribe answers and create momentum, is how will all these high-value, high-dollar, high-hope innovation sets align beyond their siloed business unit cheerleaders? Therein resides the critical determination of how "delivery stacks" are created when examining the orchestration of advanced technological building blocks into reusable offerings--compartmentalized, reusable, agile, layered and orchestratable.

Ask Yourself--What Should We Do?
So, here we find ourselves--an economy that may or may not crater in 2020 due to self-inflicted incapacitation, and corporate budgets pushed to the breaking points by trends that are outside of industry control, influence and reach. Technologies and the digital channels they are deployed into are now iterating over a period of weeks spurred by advances, security and privacy concerns and competitive actions.

As the percentage of financial data controlled by financial institutions continues to shrink (now less than 40%), where are the paths to DOC open and viable? How can the components of DOC be defined, assembled, reassembled and retired in the wake of continuous delivery brought forth by market influencers outside of industry sway?

In our need to react, we seek out partners, hire smart and cunning personnel and advisors, and we adopt solutions and methods to build them that are "industry leading" in the hope that once it is assembled, clarity and stability will present itself. Moreover, IT departments in the past decade have become fully integrated with business units often being directed in a matrixed organizational entity structure that puts traditional responsibilities and delivery demands outside the fraternity silos of "eccentric" computer and data scientists.

This is the world where large financial institution budgets exceed a billion dollars just for cybersecurity. Billions more are spent on the #five-Vs of data (velocity, veracity, volume, variety and validity) that begets billions more on analysis, alignments and now, AI. In total, the spend itself has become an AI exercise as institutions grow across a base that consumes 250 competitors each year. What should be funded, expanded or retired is exceedingly complex due to pervasive touchpoints inside and outside the financial institution.

The decades-long industry consolidation has spawned scale. Scale has brought in complexity and benefits, but how does it all fit together as demands become ephemeral and non-linear? As channels, the digital ones, become transitory against rapidly accelerating demands and personal technologies (e.g., wearables and layered apps), the waste associated with complexity are difficult to uncover as ill-defined, but similar components are put into black boxes that are only monitored for requirements and results--not what is inside.

Getting the Organization Prepared
As we can see, DOC is a new analysis process that brings forth rigor and discipline across digital channels that have been in the face of unprecedented change, viewed as unique. To find overlaps and to integrate DOCs, financial institutions need to understand and decompose the often black box solutions into transparent segments. Analogous to IT personnel dynamically capturing and managing enterprise architectures (i.e., a digital roadmap of how everything digital fits, talks, interchanges, vulnerabilities, monitoring and is upgraded), DOC "mapping," for lack of a better phrase, provides a proactive assembly and disassembly of digital channel segments, their behaviors, attributes, IoT and smart data..

To prepare the financial institution for a proactive review and projection of DOCs, buy-in from business unit leaders must be secured upfront. Whereas we have mentioned the drivers for DOC usage, a primary result will be greater control over the lifecycle of the channel, its customers and advanced decision-making information previously unavailable.

Use of DOC mapping as a key benefit to the enterprise as a solution process to enhance functionality. How? By identifying the compartments within the digital channels, reusable components can be discovered, commonality and redundancy can be addressed, future enhancements may be identified from differing departments who already have installed foundational elements, and the time-cycle of delivery can be shortened for all the obvious reasons.

Financial institutions are indeed silos, especially large ones with billions in IT expenditures. It is the lessons learned from these large enterprises that can now be transplanted into smaller financial institutions (i.e., not the "Big-9") to improve competitiveness at upgraded delivery efficiencies. Availability of mappings across the enterprise taking decision making away from business unit leaders but providing them informed alternatives.

So, here we are: managing and implementing digital omnichannels that arrive like rain in a tropical climate. The management and costs to administer and enhance these DOCs will grow non-linearly as the new decade approaches. As synthetic intelligences expand the functionalities of DOCs, the mappings will become a critical technique to adopt and adapt change requirements.

In the next segment of this series, we will examine the process techniques necessary conduct DOC "mappings" as methods to leverage investment, improve process timings and avoid cultural resistance.

(Views expressed in this article do not necessarily reflect policy of the Mortgage Bankers Association, nor do they connote an MBA endorsement of a specific company, product or service. MBA Insights welcomes your submissions. Inquiries can be sent to Mike Sorohan, editor, at msorohan@mba.org; or Michael Tucker, editorial manager, at mtucker@mba.org.)

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